An Application Of Augmented Monetary Conditions Index On The ASEAN-Five

Abstract

Previous studies have suggested Monetary Conditions Index (hereafter MCI) serves
as an indicator of the monetary policy stance to capture the degree of tightness of the
monetary policy. The weights of the MCI in the model reflect long-term effects of
the interest rate and the exchange rate on the economic activity and ultimately the
inflation. Nevertheless, MCIs may not be used as an operational target as it has
heavily been documented in the mainstream literature since it is not resilient to the
problem of shock identification. Recognizing the caveats upon its usage empirically,
the augmented MCI (AMCI) is contemplated by incorporating more informative
‘other variables’ into the conventional model which consists of two major variables
i.e., the interest rate and the exchange rate. Since monetary policy affects the price
level through a number of transmission mechanisms, other potential variables need
to be incorporated to AMCI to account for possible channels in the transmission
mechanisms. The details of “other variables” are as follows: 1) government bonds yield as proxy for long-term interest rate; 2) the real share price as proxy for asset
price channel, and 3) real claims on private sectors for credit channel. However, the
lag effects of the examined determinant variables on output are dynamics and vary,
at least in the short-term. Therefore, the main objective of this thesis is to estimate
the weight of the AMCI, and identify the lag effect on the real Gross Domestic
Product (GDP) using Autoregression Distribution Lags (ARDL) bounds test
approach for cointegration analysis as proposed by Pesaran et al., (2001).
Bounds test reveals an evidence of the long-run cointegration for all the
ASEAN-Five founder countries. This has verified the stability of the country’s GDP
demand function which is used to construct the AMCI ratio. In Indonesia, the bounds
test reveals an evidence of the long-run cointegration between the real GDP and its
determinants, namely the bond rate, the exchange rate, and the share prices from
1983:2-2004:4. Nevertheless, the claim of private sector (COPS, the proxy of credit
channel) does not appear to be a significant variable in the model. Meanwhile for
both Malaysia and Singapore, the ARDL approach validates the existence of
long-run cointegration between the GDP and the exchange rate, the bond and the
short-term interest rate, as well as the COPS over the quarterly period of
1980:1-2004:4 and 1981:1-2004:4 respectively. Nevertheless, the asset price channel
does not fit into the model significantly. While in Thailand, the bounds test reveals
an evidence of the cointegration between the real GDP and its determinants, i.e., the
interest rate, the exchange rate, and the share price over the quarterly period of
1980:1-2004:4). However, the credit channel does not reveal any significant result in the model. In the Philippines, the bounds test reveals an evidence of a cointegration
between the real GDP and the bond rate, the short-term interest rate, the exchange
rate, the COPS, and the share price that address all the key transmission mechanisms
channels in the conduct of the monetary policy, namely the interest rate channel, the
exchange rate channel, the credit channel, and the asset price channel over the
quarterly period of 1982:1-2004:4
Monetary conditions during the period under-study are found to be reflected in each of
the central banks’ reaction to the prevailing economic situation, which implies that
AMCI tracks the inversed movements of the real GDP plausibly on the average,
except during the onset of Asian financial crisis in 1997.